U.S. patent application number 13/455848 was filed with the patent office on 2013-01-24 for system for wireless location estimation using radio transceivers with polarization diversity.
The applicant listed for this patent is Tapas Chakravarty, Mariswamy Girish Chandra, Prabha Janardan, Chethan Puttanna Konanakera, Balamuralidhar Purushothaman. Invention is credited to Tapas Chakravarty, Mariswamy Girish Chandra, Prabha Janardan, Chethan Puttanna Konanakera, Balamuralidhar Purushothaman.
Application Number | 20130023283 13/455848 |
Document ID | / |
Family ID | 43922731 |
Filed Date | 2013-01-24 |
United States Patent
Application |
20130023283 |
Kind Code |
A1 |
Chakravarty; Tapas ; et
al. |
January 24, 2013 |
System for Wireless Location Estimation Using Radio Transceivers
with Polarization Diversity
Abstract
A system and method for wireless location estimation of a mobile
node using radio transceivers with polarization diversity have been
disclosed. The system includes a plurality of pre-defined fixed
reference nodes distributed over a predetermined area adapted to
transmit fixed reference signals. The system further includes
mobile node transmission module at the mobile node adapted to
transmit mobile reference signals with respect the mobile node and
plurality of pre-defined fixed reference nodes. The horizontal
polarization module and vertical polarization module polarize the
transmitted mobile reference signals and the strength of the
signals is measured. The derivation module derives the range of the
signals. Subsequently, a profile of the derived range with
reference to the measured signal strength is created by the system.
The system further employs a trilateration algorithm to determine
localization of the node using the created profile, thereby
providing the location estimation for the mobile node.
Inventors: |
Chakravarty; Tapas;
(Kolkata, IN) ; Konanakera; Chethan Puttanna;
(Tumkur, IN) ; Janardan; Prabha; (Bangalore,
IN) ; Chandra; Mariswamy Girish; (Bangalore, IN)
; Purushothaman; Balamuralidhar; (Bangalore, IN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Chakravarty; Tapas
Konanakera; Chethan Puttanna
Janardan; Prabha
Chandra; Mariswamy Girish
Purushothaman; Balamuralidhar |
Kolkata
Tumkur
Bangalore
Bangalore
Bangalore |
|
IN
IN
IN
IN
IN |
|
|
Family ID: |
43922731 |
Appl. No.: |
13/455848 |
Filed: |
April 25, 2012 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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PCT/IN2010/000695 |
Oct 27, 2010 |
|
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13455848 |
|
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Current U.S.
Class: |
455/456.1 |
Current CPC
Class: |
G01S 5/0252 20130101;
G01S 11/06 20130101; H04W 64/00 20130101; G01S 5/14 20130101 |
Class at
Publication: |
455/456.1 |
International
Class: |
H04W 24/00 20090101
H04W024/00 |
Foreign Application Data
Date |
Code |
Application Number |
Oct 30, 2009 |
IN |
2528/MUM/2009 |
Claims
1. A system for wireless location estimation of a mobile node using
radio transceivers with polarization diversity, said system
comprising: a plurality of fixed transmission modules at
pre-defined fixed reference nodes distributed over a predetermined
area adapted to transmit fixed reference signals; mobile node
transmission module at the mobile node adapted to transmit mobile
reference signals with respect to the mobile node and the plurality
of pre-defined fixed reference nodes; horizontal polarization
module adapted to horizontally polarize the transmitted mobile
reference signals; vertical polarization module adapted to
vertically polarize the transmitted mobile reference signals;
receiver module adapted to receive the horizontally polarized
signals and vertically polarized signals; measurement module
adapted to measure signal strength of the received signals;
derivation module adapted to derive range of the received signals;
profile creation module adapted to create a profile of said derived
range with reference to said measured signal strength; and
trilateration module adapted to employ a trilateration algorithm to
determine localization of said node using said created profile,
thereby provide the location estimation of said mobile node.
2. The system as claimed in claim 1 wherein, said profile creation
module includes quadrature combining module adapted to create a
profile by quadrature combining said measured signal strength from
said horizontally polarized signal and said vertically polarized
signal.
3. The system as claimed in claim 1 wherein, said profile creation
module includes polynomial fitting computation module adapted to
compute a polynomial fit for said derived profile with a
pre-defined monotonic curve as a reference curve for further use in
localization estimation.
4. The system as claimed in claim 1 wherein, said trilateration
module is a selection based trilateration module with virtual
sampling adapted to reduce the error in estimated localization of
said node.
5. A method for wireless location estimation of a mobile node using
radio transceivers with polarization diversity, said method
comprising the following steps: transmitting fixed reference
signals using a plurality of fixed transmission module at
pre-defined fixed reference nodes distributed over a predetermined
area; transmitting mobile reference signals with respect to said
mobile node and said plurality of pre-defined fixed reference nodes
with fixed reference signals using mobile node transmission module
at said mobile node; horizontally polarizing said transmitted
mobile reference signals; vertically polarizing said transmitted
mobile reference signals; receiving said horizontally polarized
signals and said vertically polarized signals; measuring signal
strength of said received signals; deriving range of said received
signals; creating a profile of said derived range with reference to
said measured signal strength; and employing a trilateration
algorithm to determine localization of said node using said created
profile, thereby provide the location estimation of said mobile
node.
6. The method as claimed in claim 5 wherein, said step of creating
a profile includes the step of creating a profile by quadrature
combining said measured signal strength from said horizontally
polarized signal and said vertically polarized signal.
7. The method as claimed in claim 5 wherein, said step of creating
a profile includes the step of computing a polynomial fit for said
derived profile with a pre-defined monotonic curve as a reference
curve for further use in localization estimation.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of PCT Patent Application
Serial Number PCT/IN2010/000695, filed on Oct. 27, 2010, entitled,
"System for Wireless Locations Estimation Using Radio Transceivers
with Polarization Diversity," which claims priority from Indian
Patent Application Serial Number 2528/MUM/2009, filed on Oct. 30,
2009.
FIELD OF DISCLOSURE
[0002] This disclosure relates to the field of wireless
transmission and reception. Particularly, this disclosure relates
to a system for wireless location estimation using radio
transceivers with polarization diversity.
BACKGROUND
[0003] Wireless sensor networks are being extensively used to study
various aspects of the physical environment which are complex in
nature. They are deployed for a wide range of applications such as
environmental monitoring, location tracking in retail chains,
gathering military intelligence, providing disaster relief, factory
instrumentation, hospital management and information tracking, and
the like. Many of these applications require the sensing of
location of individual nodes.
[0004] The technique of wireless localization, for estimating the
position of a mobile wireless node, is an area that has attracted
much attention in recent years. The following papers disclose this
in detail:
[0005] "A system for LEASE: location estimation assisted by
stationary emitters for indoor RF wireless networks"; Proc. IEEE
INFOCOM 2004, 2004; P. Krishnan, A. S. Krishnakumar, W. H. Ju, C.
Mallows, and S. Ganu,
[0006] "Locationing in distributed ad-hoc wireless sensor
networks"; IEEE International Conference on Acoustics, Speech and
Signal Processing, 2001, Salt Lake City, Utah, Volume: 4, Page(s):
2037-2040, May, 2001; C. Savarese, J. M. Rabaey, J. Beutel
[0007] "A statistical modeling versus geometrical determination
location approach for static positioning in indoor environment";
Proceedings of the International Symposium on Wireless Personal
Multimedia Communications (WPMC '05), Aalborg, Denmark, September
2005; R. Singh, L. Macchi, and C. S. Regazzoni
[0008] "An In-Building RF-based User Location and Tracking System";
INFOCOM (2) (March 2000) pp. 775-784; Paramvir Bahl, Venkata N.
Padmanabhan, RADAR
[0009] "Design and Calibration of the SpotON Ad-Hoc Location
Sensing System"; August 2001; Jeffrey Hightower, Chris Vakili,
Gaetano Borriello, and Roy Want
[0010] The most popular system, GPS as disclosed in "Special Issue
on GPS: The Global Positioning System"; Proceedings of the IEEE,
Volume 87, Number 1, pp. 3-172, January 1999; Per Enge, Pretap
Misra, uses radio time-of-flight lateration via satellites, but has
the limitation of only working outdoors.
[0011] Localization also done using sound as disclosed in "The
cricket location-support system"; 6th ACM International Conference
on Mobile Computing and Networking, August 2000; IEEE
Communications Society/WCNC 2005 2353 0-7803-8966-2/05; N. B.
Priyantha, A. Chakraborty, and H. Balakrishnan, using infrared as
disclosed in "The Active Badge Location System"; ACM Transactions
on Information Systems, Vol. 40, No. 1, pp. 91-102, January 1992;
Roy Want, Andy Hopper, Veronica Falcao, Jon Gibbons, and using
radio frequency identification (RFID) as disclosed in "Landmarc:
Indoor location sensing using active RFID" in First IEEE
International Conference on Pervasive Computing and Communications,
March 2003, pg. 407; L. M. Ni, Y. Liu, Y. C. Lau, and A. P. Patil,
relies on specialized hardwares and infrastructures which, in turn,
incur additional costs. This will prohibit the use of such schemes
in low-cost sensor nodes.
[0012] Localization is also done using radio interferometry as
disclosed in U.S. Pat. No. 7,558,583 in which the phase offsets of
the interference signal received by two receivers are measured. But
here the sources of errors like multipath fading, antenna
orientation, signal processing errors are more.
[0013] A very popular distance based single hop localization
technique is trilateration as disclosed in "Demonstrating the
effects of multi-path propagation and advantages of diversity
antenna techniques"; Proc. IEEE Ant. Propag. Symposium, 2003; K. S.
Bialkowski, A. Postula, is a method to find the position of an
object based on distance measurements to three objects with known
positions. Single-hop localization algorithms can be used in indoor
and small scale outdoor applications, however, this approach is not
scalable and requires the topology of the network to cover a very
limited area and requires precise range measurements. As the
density of nodes decrease, measurement errors increase.
[0014] Perhaps, the most important criterion of a successful
location estimation technique is the accuracy of the model. Thus
the quality indicators of the deployed system are reliability and
the error of estimate (in percentage terms) in the given area of
operation.
[0015] One of the known methods for such estimation is one using
received signal strength indicator (RSSI). RSSI based localization
systems are simple and inexpensive and can be used for indoor
environments for estimating the locations. It is known that RSSI
based localization algorithms suffer from deleterious effects of
severe multipath phenomenon in indoor environments. Elnahrawy et al
as disclosed in "The limits of localization using signal strength:
A comparative study"; Proc. IEEE SECON 2004, 2004. [6] Kamin
Whitehouse, David Culler, Macro-Calibration in Sensor/Actuator
Networks, Mobile Networks and Applications, Kluwer Academic
Publishers 2003, have investigated the fundamental limits of
localization for wireless sensor networks using received signal
strength.
[0016] The theoretical lower bounds on location estimation error
(Cramer-Rao bound) using RSSI has been derived in "Using proximity
and quantized RSS for sensor", Proc. of 2nd ACM Int. Conf. on
Wireless Sensor Network, 2003; N. Patwari and A. O. Hero III. Roos
et al as disclosed in "A statistical modeling approach to location
estimation"; IEEE Trans. Mobile Computing, 1(1), 2002, 59-69,
presented a statistical modeling framework, which enables location
estimation based on statistical power model.
[0017] The above discussion indicates that the RSSI based indoor
localization is highly researched and the roadmap to future
research indicates the requirement of an accurate model which can
enable localization with precision and minimum efforts in
deployment and measurements. For majority of instances, the
investigators have based their models only on single channel
measurements. However, use of diversity techniques is known to
improve reliability of a propagation channel. It is often seen that
diversity measurements lead to conclusions of better
signal-to-noise ratio; and thereby reliability specifically meant
for data communication. Different diversity techniques, including
polarization diversity have been described in "Bluetooth
communication employing diversity"; Proc. ISCC, 2003; F. Bektas, B.
Vondra, P. E. Veith, L. Faltin, A. Pohl and A. L. Scholtz, for
indoor communication set up.
[0018] It is thus seen, from FIG. 1 of the accompanying drawings,
that there is immense challenge in obtaining a stable RSSI Vs
distance profile for indoor environment; in particular having a
monotonic behavior. FIG. 1 shows a typical RSSI profile for a
ZigBee radio link. The variance in the RSSI values introduces error
in the location estimation while the nonmonotonic characteristic
gives raise to ambiguity. Since in real life deployment in dense
indoor environment, RSSI based distance estimation can lead to
multiple distance estimates, there is strong challenge in creating
a simple algorithm which will estimate the distance with great
accuracy.
Polarization Diversity in Indoors is Discussed Below:
[0019] It is known that RSSI can be improved using polarization
diversity. As the likelihood is that the signal will suffer some
level of attenuation, as it disperses slightly and propagates along
fading channel in a given polarization, it is known that
propagation characteristics in wireless communication systems are
different for vertically and horizontally polarized waves as
disclosed in "Spatial, polarization, and pattern diversity for
wireless handheld terminals"; Dietrich, C. B., Jr.; Dietze, K.;
Nealy, J. R.; Stutzman, W. L.; Antennas and Propagation, IEEE
Transactions on Volume 49. Multiple reflections between the
transmitter and the receiver lead to depolarization of radio waves,
coupling some energy of the transmitted signal into the orthogonal
polarized wave. Due to that characteristic of multipath radio
channel, vertically/horizontally polarized transmitted waves have
also horizontal/vertical component (i.e., additional diversity
branch).
[0020] A thorough investigation through extensive_experimentations
revealed that the packets of deep fading in one polarization often
do not coincide with that in other polarization. This phenomenon
leads to a reasonable conclusion that in indoor and a RF challenged
environment, polarization rotation is a major source of signal
attenuation.
OBJECTS
[0021] Some of the non-limiting objects of the present disclosure,
which at least one embodiment herein satisfy, are as follows:
[0022] An object of the disclosure is to accurately estimate the
position of a mobile wireless node.
[0023] Another object of the disclosure is to provide a reliable
system and method for estimating the position of a mobile wireless
node.
SUMMARY
[0024] The present disclosure envisages a system for wireless
location estimation of a mobile node using radio transceivers with
polarization diversity, the system comprising: [0025] a plurality
of fixed transmission module at pre-defined fixed reference nodes
distributed over a predetermined area adapted to transmit fixed
reference signals; [0026] mobile node transmission module at the
mobile node adapted to transmit mobile reference signals with
respect to the mobile node and the plurality of pre-defined fixed
reference nodes with fixed reference signals; [0027] horizontal
polarization module adapted to horizontally polarize the
transmitted mobile reference signals; [0028] vertical polarization
module adapted to vertically polarize the transmitted mobile
reference signals; [0029] receiver module adapted to receive the
horizontally polarized signals and the vertically polarized
signals; [0030] measurement module adapted to measure signal
strength of the received signals; [0031] derivation module adapted
to derive range of the received signals; [0032] profile creation
module adapted to create a profile of the derived range with
reference to the measured signal strength; and [0033] trilateration
module adapted to employ a trilateration algorithm to determine
localization of the node using the created profile, thereby provide
the location estimation of the mobile node.
[0034] Typically, in accordance with the present disclosure, the
profile creation module includes quadrature combining module
adapted to create a profile by quadrature combining the measured
signal strength from the horizontally polarized signal and the
vertically polarized signal.
[0035] Typically, in accordance with the present disclosure, the
profile creation module includes polynomial fitting computation
module adapted to compute a polynomial fit for the derived profile
with a pre-defined monotonic curve as a reference curve for further
use in localization estimation.
[0036] Typically, in accordance with the present disclosure, the
profile trilateration module is a selection based trilateration
module with virtual sampling adapted to reduce the error in
estimated localization of the node.
[0037] The present disclosure envisages a method for wireless
location estimation of a mobile node using radio transceivers with
polarization diversity, the method comprising the following steps:
[0038] transmitting fixed reference signals using a plurality of
fixed transmission module at pre-defined fixed reference nodes
distributed over a predetermined area; [0039] transmitting mobile
reference signals with respect to the mobile node and the plurality
of pre-defined fixed reference nodes with fixed reference signals
using mobile node transmission module at the mobile node; [0040]
horizontally polarizing the transmitted mobile reference signals;
[0041] vertically polarizing the transmitted mobile reference
signals; [0042] receiving the horizontally polarized signals and
the vertically polarized signals; [0043] measuring signal strength
of the received signals; [0044] deriving range of the received
signals; [0045] creating a profile of the derived range with
reference to the measured signal strength; and [0046] employing a
trilateration algorithm to determine localization of the node using
the created profile, thereby provide the location estimation of the
mobile node.
[0047] Typically, in accordance with the present disclosure, the
step of creating a profile includes the step of creating a profile
by quadrature combining the measured signal strength from the
horizontally polarized signal and the vertically polarized
signal.
[0048] Typically, in accordance with the present disclosure, the
step of creating a profile includes the step of computing a
polynomial fit for the derived profile with a pre-defined monotonic
curve as a reference curve for further use in localization
estimation.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS
[0049] The System for wireless location estimation using radio
transceivers with polarization diversity will now be described with
reference to the non-limiting, accompanying drawings, in which:
[0050] FIG. 1 illustrates a Typical RSSI profile for a ZigBee radio
link;
[0051] FIG. 2 illustrates Derived path loss (by measurement) and
comparison with free-space path loss;
[0052] FIG. 3 of the accompanying drawings, displays the derived
curve as well as the predicted curve;
[0053] FIG. 4 illustrates a Schematic implementation of a typical
node with dual Radios for the communication node; and
[0054] FIG. 5 illustrates the experimental setup for localization,
in accordance with the present disclosure.
DETAILED DESCRIPTION OF THE ACCOMPANYING DRAWINGS
[0055] In accordance with the present disclosure, there is
envisaged a system and scheme for wireless location estimation
based on a derived profile from received signal strengths, measured
in multiple antenna polarizations as a calibration data, in
conjunction with an enhanced trilateration algorithm to improve the
accuracy of the location estimate.
[0056] According to this disclosure, there is envisaged a
significant improvement in robust RSSI estimation using dual radio
system at the reference nodes by observing simultaneously the
received signal strength from a transmitting node, which may be
mobile node, employing horizontal and vertically polarized antennas
respectively. The measured RSSI at two polarizations at each
reference node are combined optimally to generate a derived range
versus signal strength profile which has near monotonic
characteristics. The derived RSSI profile at each reference node is
used as a range calibration data for further estimation of the
mobile node location using an enhanced trilateration algorithm.
[0057] In accordance with the present disclosure, the system for
wireless location estimation of a mobile node includes a plurality
of fixed transmission modules at pre-defined fixed reference nodes
which are distributed over a predetermined geographical area. The
fixed reference nodes are adapted to transmit fixed reference
signals.
[0058] In accordance with the present disclosure, the mobile node
includes mobile node transmission module adapted to transmit mobile
reference signals with respect to the location of the mobile node
and the plurality of pre-defined fixed reference nodes, The system
further includes a horizontal polarization module adapted to
horizontally polarize the transmitted mobile reference signals and
a vertical polarization module adapted to vertically polarize the
transmitted mobile reference signals,
[0059] The system, in accordance with the present disclosure
further includes a receiver module adapted to receive the
horizontally polarized signals and vertically polarized signals
from the horizontal polarization module and the vertical
polarization module respectively.
[0060] The system, in accordance with the present disclosure
further includes a measurement module adapted to measure the signal
strength corresponding to the received signals, The system, in
accordance with the present disclosure includes a derivation module
which is adapted to derive the range corresponding to the received
signals.
[0061] The profile creation module creates a profile which includes
at least the derived range of the received signals. The range of
the received signals is measured with reference to the measured
signal strength. The system further includes a trilateration module
which is adapted to employ a trilateration algorithm to determine
the localization of the mobile node using the profile created by
the profile creation module, thereby providing the location
estimation corresponding to the mobile node.
[0062] The profile creation module, in accordance with the present
disclosure includes a quadrature combining module adapted to create
a profile by quadrature combining the strengths of the horizontally
polarized signal and vertically polarized signal.
[0063] The profile creation module, in accordance with the present
disclosure further includes a polynomial fitting computation module
which is adapted to compute a polynomial fit for the derived
profile with a pre-defined monotonic curve as a reference curve for
further use in the localization estimation.
[0064] In accordance with the present disclosure, the trilateration
module is a selection based trilateration module with virtual
sampling. The trilateration module is adapted to reduce the error
in estimated localization of the mobile node.
[0065] Still particularly, the system of this disclosure envisaged
to use a novel methodology for robust wireless location estimation
in following steps: [0066] a) Generation of a derived RSSI profile
by quadrature combining the RSSI measurements from simultaneous
transmissions in two polarizations [0067] b) Generation of a
polynomial fit for the derived RSSI profile with an error margin to
get a monotonic curve as a reference curve for further use in
location estimation [0068] c) Use of a novel algorithm "Selection
based trilateration algorithm with virtual sampling (STAVS)" to
reduce the error in estimated location of the target.
[0069] In accordance with this disclosure, there is described a new
technique for indoor localization to reduce the estimated range
error introduced by interference and/or path loss; where the
cumulative errors is controlled substantially as compared to other
existing techniques.
[0070] The disclosure exploits the polarization diversity by using
dual radio system at the reference node to obtain a robust RSSI.
This method reduces the variance of multiple RSSI measurements
corresponding to a specific distance from the transmitter.
[0071] An RSSI Vs Distance profile is generated through
experimentation for each polarization. A derived profile is
generated by combining the signal strengths in two polarizations
using the following formula
S.sub.d=10 log.sub.10 { {square root over
(S.sub.V.sup.2+S.sub.H.sup.2)}} (1)
Where,
[0072] S.sub.V--RSSI received in vertical polarization (with
transmission also in same polarization) S.sub.H--RSSI received in
horizontal polarization (with transmission also in same
polarization) S.sub.d--Derived RSSI profile
[0073] FIG. 2 of the accompanying drawings shows S.sub.v, S.sub.h,
and S.sub.d for a typical measurement.
[0074] The derived profile with the quadrature combining of the
signal in both polarizations will have a reduced variance
corresponding to repeated measurements at a specific distance. The
variance is typically within .+-.3 db. Subsequently the derived
Signal profile (S.sub.d) is fitted with a (1-n) polynomial taking
care of this variance to get a reference curve for propagation path
loss, S.
[0075] The propagation path loss is predicted as follows:
S.sub.f=y.sub.0+a ln(d)(dB) (2)
Where, d is range in m Here the values of the constant depend on
the environment. For example, inside a typical office space,
y.sub.0.about.-42 to -44 dB and a .about.-11.5 to -12.5
[0076] FIG. 3 of the accompanying drawings, displays the derived
curve as well as the predicted curve. The derived path loss (using
eq. 1) and the predicted path loss (using eq. 2) are shown.
[0077] The reference curve obtained by the polynomial fit described
above will be used for the new Selection based Trilateration
Algorithm with Virtual Sampling (STAVS). The detail of the STAVS
algorithm is described below.
[0078] Selection based Tri-lateration Algorithm with Virtual
Sampling (STAVS) is described as below:
[0079] The reference profile generated by the polynomial fitting of
S.sub.d is used for estimating the range corresponding to a derived
RSSI value. It has been stated earlier that any derived point
measurements of RSSI (using polarization diversity) will generally
have a variance and that could be of the order of a maximum of 3
dB. So the ideal value of the RSSI (in the absence of any fading)
can be assumed to be randomly distributed within an interval of
.+-.3 dB. This information is used to generate additional virtual
RSSI samples falling within this interval.
[0080] It is known that for trilateration at least three reference
nodes are required to estimate the absolute location of a
transmitter (of the mobile node). Distances of the mobile node from
three reference nodes are estimated from the reference curve. There
will be one distance value for each of the virtual RSSI
samples.
[0081] The distance estimation is done by using eq 2, where we
consider that the derived RSSI as per eq. 1 (S.sub.d) is same as
S.sub.f as in eq. 2. Then using eq. 2, the distance `d` is
computed.
[0082] Use of more than three reference nodes provides additional
measurement samples enabling a better estimate. Let us consider
four reference nodes <N1,N2,N3,N4> and let
<d1,d2,d3,d4> be the corresponding distances of the mobile
node (from those reference nodes respectively) Now any triplet
combination of the distances d1,d2,d3,d4 can be used to estimate
the absolute location of the mobile node. That is the triangles
formed by the triplets <d1, d2, d3>, <d1, d3, d4>,
<d1, d2, d4>, <d2, d3, d4> can be used for location
estimation of the mobile node using trilateration.
[0083] It can be seen that the estimation error for a location
within the triangle formed by the triplet is less than that
corresponding to a location outside the triangle. Therefore if the
location estimated from a triplet falls outside the corresponding
triangle then that may be discarded because of they are
comparatively more noise prone. This is the basic idea behind
selection based trilateration.
[0084] Finally all selected location data <xi,yi> from STAVAS
is averaged to find the final estimated location <X,Y> of the
mobile node.
[0085] The system's implementation is described below:
[0086] A system of radio transceivers involving a set of reference
nodes (fixed with known positions) is deployed to cover an area and
a mobile radio within the designated area for which the position
needs to be estimated.
[0087] All the nodes involved in the above system have the
capability to work in two polarizations. The receiving nodes will
have two receivers with antennas connected in different
polarizations (Vertical & Horizontal). Transmitter will have
two antennas in different polarizations and can transmit in one
polarization at a time.
[0088] Implementation of dual radio system for the communication
node is shown FIG. 4. The figure depicts that each reference node
has two radio systems one in horizontal polarization and another in
vertical polarization.
[0089] As shown in FIG. 4, each of the reference nodes has two
separate transceivers. One transceiver (Radio 1) works in vertical
polarization and another transceiver (Radio 2) works in horizontal
polarization. The processor communicably coupled to radio 1 and
radio 2 measures the signal strength from each polarization and
combines them using equation 1 and transmits that RSSI values to a
sink node while adding its node ID with the information. The next
section will discuss about experimental setup of the work being
carried out.
[0090] Indoor localization technologies have been developed on
various concepts and aspects. Here it is considered that the
placements of nodes are in a regular geometrical shape rectangle,
in this phase reference nodes are placed at the corners of the
rectangle and carry out the experiment. There are four reference
nodes which are placed at four corners of the working room as shown
FIG. 5 of the accompanying drawings Each reference node has two
radios one for horizontal polarization and another for vertical
polarization as shown in FIG. 4.
[0091] From FIG. 5, it can be seen that R1, R2, R3, R4 are the
reference nodes (positions of these reference nodes are known),
placed at four corners of the room and Target node for which the
position needs to be estimated. All the reference nodes are assumed
to be fixed and target node can be moved to obtain new set of its
location estimation result (since the position of the target is
unknown we can place this node at any place in the given area and
run the algorithm to obtain the new target location). All reference
and target nodes support dual radio system and are capable of
sending the data to sink node. Once data from all the reference
node has been received at the sink, the localization algorithm will
be run (on the sink node) and the coordinates of the target node
will be found out, which is discussed in next section:
[0092] The Methodology of localization in accordance with this
disclosure is described. The steps involved in the wireless
localization which have been described in earlier sections are as
below:
Initial Setup Procedure
[0093] Step 0: Generation of RSSI profile
This step is for calibration and needs to done only once or
periodically [0094] A. Generate the distance Vs RSSI profile with
measurements in multiple polarizations and prepare a derived RSSI
profile by quadrature combining as detailed in section 3. [0095] B.
Generate a Reference RSSI profile using a polynomial fit to the
derived profile.
Localization
[0096] Step 1: Configure the mobile node to broadcast the
specialized message periodically. The RSSI value corresponding to
the reference node is routed to a sink node.
[0097] Step 2: The sink node adds .+-.3 dB offset values to the
derived RSSI value received from each node and stores as S.sub.d
(i,1) . . . S.sub.d (i, 7) where `i` stands for the ith node and
each node represents seven (typical) RSSI values with one
measurement, i.e, by incorporating the offset.
[0098] Step 3: Run the STAVS algorithm at the sink node to estimate
the location of the mobile node.
[0099] The present disclosure envisages a method for wireless
location estimation of a mobile node using radio transceivers with
polarization diversity. The method, in accordance with the present
disclosure includes the following steps: [0100] transmitting fixed
reference signals using a plurality of fixed transmission module at
pre-defined fixed reference nodes distributed over a predetermined
area; [0101] transmitting mobile reference signals with respect to
the mobile node and the plurality of pre-defined fixed reference
nodes with fixed reference signals using mobile node transmission
module at the mobile node; [0102] horizontally polarizing the
transmitted mobile reference signals; [0103] vertically polarizing
the transmitted mobile reference signals; [0104] receiving the
horizontally polarized signals and the vertically polarized
signals; [0105] measuring signal strength of the received signals;
[0106] deriving range of the received signals; [0107] creating a
profile of the derived range with reference to the measured signal
strength; and [0108] employing a trilateration algorithm to
determine localization of the node using the created profile,
thereby provide the location estimation of the mobile node.
[0109] In accordance with the present disclosure, the step of
creating a profile further includes the step of creating a profile
by quadrature combining the measured signal strength from the
horizontally polarized signal and the vertically polarized
signal.
[0110] In accordance with the present disclosure, the step of
creating a profile further includes the step of computing a
polynomial fit for the derived profile with a pre-defined monotonic
curve as a reference curve for further use in localization
estimation.
[0111] The foregoing description of the specific embodiments will
so fully reveal the general nature of the embodiments herein that
others can, by applying current knowledge, readily modify and/or
adapt for various applications such specific embodiments without
departing from the generic concept, and, therefore, such
adaptations and modifications should and are intended to be
comprehended within the meaning and range of equivalents of the
disclosed embodiments. It is to be understood that the phraseology
or terminology employed herein is for the purpose of description
and not of limitation. Therefore, while the embodiments herein have
been described in terms of preferred embodiments, those skilled in
the art will recognize that the embodiments herein can be practiced
with modification within the spirit and scope of the embodiments as
described herein.
[0112] Throughout this specification the word "comprise", or
variations such as "comprises" or "comprising", will be understood
to imply the inclusion of a stated element, integer or step, or
group of elements, integers or steps, but not the exclusion of any
other element, integer or step, or group of elements, integers or
steps.
[0113] The use of the expression "at least" or "at least one"
suggests the use of one or more elements or ingredients or
quantities, as the use may be in the embodiment of the invention to
achieve one or more of the desired objects or results.
[0114] Any discussion of documents, acts, materials, devices,
articles or the like that has been included in this specification
is solely for the purpose of providing a context for the invention.
It is not to be taken as an admission that any or all of these
matters form part of the prior art base or were common general
knowledge in the field relevant to the invention as it existed
anywhere before the priority date of this application.
[0115] While considerable emphasis has been placed herein on the
particular features of this disclosure, it will be appreciated that
various modifications can be made, and that many changes can be
made in the preferred embodiment without departing from the
principles of the disclosure. These and other modifications in the
nature of the disclosure or the preferred embodiments will be
apparent to those skilled in the art from the disclosure herein,
whereby it is to be distinctly understood that the foregoing
descriptive matter is to be interpreted merely as illustrative of
the disclosure and not as a limitation.
* * * * *